AI RESEARCH
DisRFM: Polar Riemannian Flow Matching for Structure-Preserving Graph Domain Adaptation
arXiv CS.LG
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ArXi:2602.00656v2 Announce Type: replace Graph Domain Adaptation (GDA) aims to transfer graph classifiers across domains with both semantic and topological shifts. Existing Euclidean adversarial methods face two challenges: Structural Degeneration, where domain confusion entangles and suppresses label-relevant topology, and Optimization Instability, where minimax